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Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction.

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Presentation on theme: "Customer Satisfaction/Loyalty Turna Koksal. Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction."— Presentation transcript:

1 Customer Satisfaction/Loyalty Turna Koksal

2 Goal Characterize the customer of a bank Customer satisfaction Customer loyalty Relationship between satisfaction and loyalty

3 Domain Collection of answers given to survey questions by customers 6500 customer records 174 attributes

4 Method Association rules –Relationships among items in dataset WEKA –Apriori algorithm

5 Implementation Data cleaning –MS Excel –Clean data (Derived attributes) Attribute selection –WEKA –Information gain algorithm Top 15 attributes (>0.15)

6 Implementation (cont.) Data transformation –Transform attributes into nominal values –Attribute values 1 to 7 and 99 –Group into 4: {1,2,3}  1 {4,5}  2 {6,7}  3 {99}  4 –Divide into 6 groups Attribute QTA : A,B,C,D,E,F

7 Implementation (cont.) Data transformation –Divide data into training (70%) & testing (30%) –Transform training file into.arff format Rule properties –Generate 20 rules for each group –Minimum confidence: 0.8 –Minimum support: 0.45

8 Dataset Rule Q2_01=3 ==> Q2_03=3 Information on site arranged logically = {strongly agree, agree} Trust bank to protect privacy & confidential info = {strongly agree, agree} Accuracy: 60.86%  

9 Group A Rule Q20=3 ==> Q2_03=3 How satisfied with online services {extremely satisfied, very satisfied} Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy: 53.83%  

10 Group B Rule Q2_01=3 ==> Q2_03=3 Information on site arranged logically {strongly agree, agree} Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy:62.98 %  

11 Group C Rule Q48=3 ==> Q49_02=3 Overall satisfaction with bank {extremely satisfied, very satisfied} Remain customer {extremely likely, very likely} Accuracy: 49.23%  

12 Group D Rule Q2_01=3 ==> Q2_03=3 Information on site arranged logically {strongly agree, agree} Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy: 58.12%  

13 Group E Rule Q2_01=3 Q2_06=3 ==> Q2_03=3 Information on site arranged logically {strongly agree, agree} bank.com helps me take charge of my finances {strongly agree, agree} Trust bank to protect privacy & confidential info {strongly agree, agree} Accuracy: 54.29% &  

14 Group F Rule Q1_01=3 ==> Q49_02=3 Web site overall {extremely satisfied, very satisfied} Remain customer {extremely likely, very likely} Accuracy: 51.22%  

15 Next-Steps Try different methods and compare the results Spend more time on data cleaning, preparation and transformation


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